Conjoint measurement
Conjoint measurement is the measurement of a variable that is made up of a combination of other variables which themselves affect the item being evaluated. In the physical world measurement when combining two quantiities is often simply a matter of addition. The weight of two bricks for example is easily calculated. In psychology however the situation is often more complex and variables interact. See also *Bradeley-Terry-Luce model *Experimental design *Psychometrics *Measurement theory *Rasch model *Statistical analysis References Achter, J. A. (1998). Investigating antecedents to the development of competence and fulfillment among intellectually gifted adolescents: The validity of conjointly applying above-level ability and preference assessment for early educational and career planning. Dissertation Abstracts International: Section B: The Sciences and Engineering. *Aiman-Smith, L., Scullen, S. E., & Barr, S. H. (2002). Conducting studies of decision making in organizational contexts: A tutorial for pollicy-capturing and other regression-based techniques: Organizational Research Methods Vol 5(4) Oct 2002, 388-414. *Alba, J. W., & Cooke, A. D. J. (2004). When Absence Begets Inference in Conjoint Analysis: Comment: Journal of Marketing Research Vol 41(4) Nov 2004, 382-387. *Allenby, G. M., Arora, N., & Ginter, J. L. (1995). Incorporating prior knowledge into the analysis of conjoint studies: Journal of Marketing Research Vol 32(2) May 1995, 152-162. *Allenby, G. M., & Ginter, J. L. (1995). Using extremes to design products and segment markets: Journal of Marketing Research Vol 32(4) Nov 1995, 392-403. *Anderson, N. H. (1971). An exchange on functional and conjoint measurement: Comment: Psychological Review Vol 78(5) Sep 1971, 457. *Anderson, N. H. (1971). An exchange on functional and conjoint measurement: Reply: Psychological Review Vol 78(5) Sep 1971, 458. *Bakken, D., & Frazier, C. L. (2006). Conjoint analysis: Understanding consumer decision making. Thousand Oaks, CA: Sage Publications, Inc. *Bontempo, R. N., Bottom, W. P., & Weber, E. U. (1997). Cross-cultural differences in risk perception: A model-based approach: Risk Analysis Vol 17(4) Aug 1997, 479-488. *Bouyssou, D., & Pirlot, M. (2002). Nontransive decomposable conjoint measurement: Journal of Mathematical Psychology Vol 46(6) Dec 2002, 677-703. *Bouyssou, D., & Pirlot, M. (2004). 'Additive difference' models without additivity and subtractivity: Journal of Mathematical Psychology Vol 48(4) Aug 2004, 263-291. *Bouyssou, D., & Pirlot, M. (2004). Preferences for multi-attributed alternatives: Traces, dominance, and numerical representations: Journal of Mathematical Psychology Vol 48(3) Jun 2004, 167-185. *Bradlow, E. T., Hu, Y., & Ho, T.-H. (2004). A Learning-Based Model for Imputing Missing Levels in Partial Conjoint Profiles: Journal of Marketing Research Vol 41(4) Nov 2004, 369-381. *Bradlow, E. T., Hu, Y., & Ho, T.-H. (2004). Modeling Behavioral Regularities of Consumer Learning in Conjoint Analysis: Reply: Journal of Marketing Research Vol 41(4) Nov 2004, 392-396. *Braithwaite, J. J., Perez-Aquino, K., & Townsend, M. (2004). In search of magnetic anomalies associated with haunt-type experiences: Pulses and patterns in dual time-synchronized measurements: Journal of Parapsychology Vol 68(2) Fal 2004, 255-288. *Butterworth, A., Sadler, L., Knowles, T. G., & Kestin, S. C. (2004). Evaluating possible indicators of insensibility and death in cetacea: Animal Welfare Vol 13(1) Feb 2004, 13-17. *Camm, J. D., Cochran, J. J., Curry, D. J., & Kannan, S. (2006). Conjoint optimization: An exact branch-and-bound algorithm for the share-of-choice problem: Management Science Vol 52(3) Mar 2006, 435-447. *Carroll, J. D., & Green, P. E. (1995). Psychometric methods in marketing research: I. Conjoint analysis: Journal of Marketing Research Vol 32(4) Nov 1995, 385-391. *Chan, F., Wang, M.-H., Thomas, K. R., Chan, C. C. H., Wong, D. W., Lee, G., et al. (2002). Conjoint Analysis in Rehabilitation Counseling Research: Rehabilitation Education Vol 16(2) 2002, 179-195. *Damon, R. Y., & Rouzies, D. (1999). Internal validity of conjoint analysis under alternative measurement procedures: Journal of Business Research Vol 46(1) Sep 1999, 67-81. *Danaher, P. J. (1997). Using conjoint analysis to determine the relative importance of service attributes measured in customer satisfaction surveys: Journal of Retailing Vol 73(2) Sum 1997, 235-260. *Dellaert, B. G. C., Arentze, T. A., Bierlaire, M., Borgers, A. W. J., & Timmermans, H. J. P. (1998). Investigating consumers' tendency to combine multiple shopping purposes and destinations: Journal of Marketing Research Vol 35(2) May 1998, 177-188. *Dellaert, B. G. C., Borgers, A. W. J., & Timmermans, H. J. P. (1997). Conjoint models of tourist portfolio choice: Theory and illustration: Leisure Sciences Vol 19(1) Jan-Mar 1997, 31-58. *Ding, M., Grewal, R., & Liechty, J. (2005). Incentive-Aligned Conjoint Analysis: Journal of Marketing Research Vol 42(1) Feb 2005, 67-82. *Dunn, J. C., & James, R. N. (2003). Signed difference analysis: Theory and application: Journal of Mathematical Psychology Vol 47(4) Aug 2003, 389-416. *Evans, R. H. (1996). An analysis of criterion variable reliability in conjoint analysis: Perceptual and Motor Skills Vol 82(3, Pt 1) Jun 1996, 988-990. *Flach, S. D., & Diener, A. (2004). Eliciting patients' preferences for cigarette and alcohol cessation: An application of conjoint analysis: Addictive Behaviors Vol 29(4) Jun 2004, 791-799. *Gan, C. E. (1993). A conjoint analysis of wetland-based recreation: A case study of Louisiana waterfowl hunting: Dissertation Abstracts International. *Green, P. E., Krieger, A. M., & Carroll, J. D. (1987). Conjoint analysis and multidimensional scaling: A complementary approach: Journal of Advertising Research Vol 27(5) Oct-Nov 1987, 21-27. *Haaijer, R., Kamakura, W., & Wedel, M. (2001). The "no-choice" alternative in conjoint choice experiments: International Journal of Market Research Vol 43(1) 2001, 93-106. *Heisterkamp, G., & Ware, R. C. (2002). Self-Movement and Conjoint Movement: Selbstpsychologie: Europaische Zeitschrift fur psychoanalytische Therapie und Forschung/ Self Psychology: European Journal for Psychoanalytic Therapy and Research Vol 3(10) 2002, 440-464. *Heller, J. (2003). Generalized factorizable automorphisms in n-component conjoint structures: Journal of Mathematical Psychology Vol 47(5-6) Oct-Dec 2003, 527-537. *Ho, Y.-X., Landy, M. S., & Maloney, L. T. (2008). Conjoint measurement of gloss and surface texture: Psychological Science Vol 19(2) Feb 2008, 196-204. *Hofstede, F., Kim, Y., & Wedel, M. (2002). Bayesian prediction in hybrid conjoint analysis: Journal of Marketing Research Vol 39(2) May 2002, 253-261. *Hubner, R., & Ellermeier, W. (1993). Additivity of loudness across critical bands: A critical test: Perception & Psychophysics Vol 54(2) Aug 1993, 185-189. *Jedidi, K., & Zhang, Z. J. (2002). Augmenting conjoint analysis to estimate consumer reservation price: Management Science Vol 48(10) Oct 2002, 1350-1368. *Jones, R. A. (1993). Modelling consumer preferences for campground design features and price using conjoint analysis: Dissertation Abstracts International. *Karabatsos, G., & Ullrich, J. R. (2002). Enumerating and testing conjoint measurement models: Mathematical Social Sciences Vol 43(3) Jul 2002, 485-504. *Krantz, D. H. (1964). Conjoint measurement: The Luce-Tukey axiomatization and some extensions: Journal of Mathematical Psychology 1(2) 1964, 248-277. *Krantz, D. H., & Tversky, A. (1971). An exchange on functional and conjoint measurement: Reply: Psychological Review Vol 78(5) Sep 1971, 458. *Luce, R. D. (1966). Two extensions of conjoint measurement: Journal of Mathematical Psychology 3(2) 1966, 348-370. *Luce, R. D., & Tukey, J. W. (1964). Simultaneous conjoint measurement: A new type of fundamental measurement: Journal of Mathematical Psychology 1(1) 1964, 1-27. *Moskowitz, H., Itty, B., & Ewald, J. (2003). Teens on the Internet: Commercial application of a deconstructive analysis of 'teen zine' features: Journal of Consumer Behaviour Vol 2(3) Mar 2003, 296-310. *Mulye, R. (1998). An empirical comparison of three variants of the AHP and two variants of conjoint analysis: Journal of Behavioral Decision Making Vol 11(4) Dec 1998, 263-280. *Niebergall, A., & Schulz, U. (1996). The use of conjoint analysis to evaluate expert ratings in personnel selection: Zeitschrift fur Arbeits- und Organisationspsychologie Vol 40(1) 1996, 38-41. *Noell, G. H., & Gresham, F. M. (2001). A multiple-sequence variant of the multiple-baseline design: A strategy for analysis of sequence effects and treatment comparison: School Psychology Quarterly Vol 16(2) Sum 2001, 207-221. *Oppewal, H., Louviere, J. J., & Timmermans, H. J. P. (1994). Modeling hierarchical conjoint processes with integrated choice experiments: Journal of Marketing Research Vol 31(1) Feb 1994, 92-105. *Oppewal, H., Louviere, J. J., & Timmermans, H. J. P. (2000). Modifying conjoint methods to model managers' reactions to business environmental trends: An application to modeling retailer reactions to sales trends: Journal of Business Research Vol 50(3) Dec 2000, 245-257. *Paulson, J. A. (1991). Is psychological measurement empirically possible? : PsycCRITIQUES Vol 36 (12), Dec, 1991. *Pelton, T. W., & Bunderson, C. V. (2003). The Recovery of the Density Scale using a Stochastic Quasi-Realization of Additive Conjoint Measurement: Journal of Applied Measurement Vol 4(3) 2003, 269-281. *Picon, E. (2004). A Monte Carlo comparison of three metric conjoint segmentation methods: Psicologica Vol 25(2) 2004, 231-252. *Picon Prado, E., & Varela Mallou, J. (2000). Segmenting markets with conjoint analysis: An application to tourism: Psicothema Vol 12(Suppl2) 2000, 453-458. *Poortinga, W., Steg, L., Vlek, C., & Wiersma, G. (2003). Household preferences for energy-saving measures: A conjoint analysis: Journal of Economic Psychology Vol 24(1) Feb 2003, 49-64. *Prieto, G., & Delgado, A. R. (2003). Rasch-modelling: a test: Psicothema Vol 15(1) Feb 2003, 94-100. *Rao, V. R. (2004). Comments on Conjoint Analysis with Partial Profiles: Journal of Marketing Research Vol 41(4) Nov 2004, 388-389. *Roskies, R. (1965). A measurement axiomization for an essentially multiplicative representation of two factors: Journal of Mathematical Psychology 2(2) 1965, 266-276. *Rubin, D. B. (2004). Design and Modeling in Conjoint Analysis with Partial Profiles: Comment: Journal of Marketing Research Vol 41(4) Nov 2004, 390-391. *Ryan, M. (1999). Using conjoint analysis to take account of patient preferences and go beyond health outcomes: An application to in vitro fertilisation: Social Science & Medicine Vol 48(4) Feb 1999, 535-546. *Sandor, Z., & Wedel, M. (2002). Profile Construction in Experimental Choice Designs for Mixed Logit Models: Marketing Science Vol 21(4) Fal 2002, 455-475. *Sapede, C., & Girod, I. (2002). Willingness of adults in Europe to pay for a new vaccine: The application of discrete choice-based conjoint analysis: International Journal of Market Research Vol 44(4) 2002, 463-476. *Sethuraman, R., Kerin, R. A., & Cron, W. L. (2005). A field study comparing online and offline data collection methods for identifying product attribute preferences using conjoint analysis: Journal of Business Research Vol 58(5) May 2005, 602-610. *Shamir, M., & Shamir, J. (1995). Competing values in public opinion: A conjoint analysis: Political Behavior Vol 17(1) Mar 1995, 107-133. *Spoth, R., & Redmond, C. (1993). Identifying program preferences through conjoint analysis: Illustrative results from a parent sample: American Journal of Health Promotion Vol 8(2) Nov-Dec 1993, 124-133. *Srinivasan, V., & Park, C. S. (1997). Surprising robustness of the self-explicated approach to customer preference structure measurement: Journal of Marketing Research Vol 34(2) May 1997, 286-291. *Suck, R. (2001). The normal distribution derived from qualitative conditions: Journal of Mathematical Psychology Vol 45(2) Apr 2001, 370-388. *Toubia, O., Hauser, J. R., & Simester, D. I. (2004). Polyhedral Methods for Adaptive Choice-Based Conjoint Analysis: Journal of Marketing Research Vol 41(1) Feb 2004, 116-131. *von Stefan Hoft, R. (2005). Review of ALASCA--A computer-based tool for decision-making and utility analysis: Zeitschrift fur Personalpsychologie Vol 4(2) 2005, 86-91. *Vriens, M., van der Scheer, H. R., Hoekstra, J. C., & Bult, J. R. (1998). Conjoint experiments for direct mail response optimization: European Journal of Marketing Vol 32(3-4) 1998, 323-339. *Weiner, J. L. (1994). Alternative conjoint analysis techniques: Implications for marketing research. Dissertation Abstracts International Section A: Humanities and Social Sciences. Category:Statistical measurement External links *Discussion of Rasch model